Description Usage Arguments Author(s) Examples
Calculate predictors from MSG cloud masked data
1 2 3 4 |
scenerasters |
A raster stack of cloud masked MSG scenes with non clouded areas were set to NA |
model |
A rfe object Optional. Can be used instad of the spectral,texture, pptext,zonstat,shape parameters. Variables included in the optimal model are the calculated. |
useOptimal |
if is.null(model): Logical. Use the optimal variables from rfe or those less variables which lead to a model performance within one sd of the optimal model? |
spectral |
A character vector indicating the msg channels to be included. Possible values: "VIS0.6","VIS0.8","NIR1.6","IR3.9","WV6.2","WV7.3","IR8.7", "IR9.7","IR10.8","IR12.0","IR13.4","T0.6_1.6","T6.2_10.8","T7.3_12.0", "T8.7_10.8","T10.8_12.0", "T3.9_7.3","T3.9_10.8" |
sunzenith |
A raster of the sun zenith values |
texture |
data frame of all spectral and texture combinations ("mean", "variance", "homogeneity", "contrast", "dissimilarity", "entropy","second_moment") and filter sizes which are to be calculated. (Tip: Use expand.grid to create this data.frame) |
pptext |
data frame of all spectral and texture combinations which are to be calculated for teh overall cloud entity. (Tip: Use expand.grid to create this data.frame) |
zonstat |
data frame of all spectral and zonal stat ("mean","min","max","sd") combinations (min,max,mean or sd) which are to be calculated for the overall cloud entity. (Tip: Use expand.grid to create this data.frame) |
filterstat |
data.frame of all spectral and "mean","min","max","sd" and filter size combinations |
shape |
geoemtry variables which should be included. Possible values are "Ar",SI","CA","Ur","CAI","PAR","distEdges","Re","Ru","OIC", CI1","CO1","CI2","CO2","CCI1","CCI2","CO","SHD","C1","E", "TR","CR","C2","FR","EI","SF1","GSI","SF2","C3","SF3" |
further |
a character vector including Currently "jday" and/or
"sunzenith" which will also be used as variables.
see |
date |
Date of the msg scene in format yyyymmddhhmm. Only imprtant if the day of the year (jday) is calculated (see param "further"). |
x_min |
see |
x_max |
see |
Hanna Meyer
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ############################################################################
#Example 1: Predictors from predictor list
############################################################################
# stack the msg scenes:
msg_example <-getChannels(inpath=system.file("extdata/msg",package="Rainfall"))
# raster the sunzenith
sunzenith<-getSunzenith(inpath=system.file("extdata/msg",package="Rainfall"))
#get Date
date <- getDate(system.file("extdata/msg",package="Rainfall"))
#calculate variables (takes some time...)
pred <- calculatePredictors(msg_example,
sunzenith=sunzenith,
spectral=c("VIS0.6","VIS0.8","NIR1.6","T0.6_1.6","T6.2_10.8"),
texture=expand.grid(c("NIR1.6","T6.2_10.8"),
c("variance", "contrast"),c(3,9)),
pptext=expand.grid("T3.9_10.8",c("variance","mean")),
shape=c("Ar","CAI","SI","CI1"),
filterstat=expand.grid(c("VIS0.6","T6.2_10.8"),
c("min", "max"),c(3,9)),
zonstat=data.frame("spec"=c("VIS0.8","VIS0.8","T6.2_10.8"),
"var"=c("min","sd","max")),
date=date)
print(pred)
############################################################################
#Example 2:calculate predictors from an rfe model
############################################################################
#' # stack the msg scenes:
msg_example <-getChannels(inpath=system.file("extdata/msg",package="Rainfall"))
data(rfeModel)
pred<-calculatePredictors(msg_example,model=rfeModel,date=NULL,sunzenith=NULL)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.